dev-pipeline

What This Skill Does

The dev-pipeline skill acts as an orchestrator for structured software development within the OpenClaw AI ecosystem. It bridges the gap between project management, version control, and AI-assisted coding by formalizing the software development lifecycle (SDLC). By integrating version-manager for baseline tracking and project-manager for task status, it ensures that every code change is intentional, versioned, and documented. The pipeline follows a rigorous process from initialization and architectural analysis to automated coding, review, and archival.

Installation

To integrate this skill into your environment, execute the following command in your terminal: clawhub install openclaw/skills/skills/cwyhkyochen-a11y/dev-pipeline

Use Cases

• Project Initialization: Automate the creation of directory structures and version-controlled metadata for new project iterations.
• Architectural Planning: Leverage Claude Opus 4.6 to generate comprehensive DEV_PLAN.md documents based on initial requirements.
• Iterative Development: Systematic execution of complex software tasks with built-in review loops, ensuring code quality and task-to-file mapping.
• Release Management: Automate the archiving and changelog generation process, reducing human error during deployment cycles.

Example Prompts

1. "@dev-pipeline init v2.0.0 --from v1.9.0"
2. "@dev-pipeline analyze"
3. "@dev-pipeline write --task-id T005"

Tips & Limitations

• Strict Formatting: The skill relies on specific Markdown outputs from the LLM. If the generated plan deviates from the requested task table structure, the pipeline may fail to parse the next steps.
• Manual Review: While the automation is powerful, the pending_confirm state is critical. Always audit the DEV_PLAN.md before approving execution to prevent unauthorized architectural changes.
• Dependency Tracking: Always ensure tasks follow the defined dependency logic to avoid deployment blockers in the write phase.
• Context Window: Since the pipeline relies on cumulative documentation, keep requirements files concise to avoid performance degradation in the analysis phase.